Session Information

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sessionInfo(package=NULL)
R version 3.3.2 (2016-10-31)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252    LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                           LC_TIME=English_United States.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] plyr_1.8.4  readr_1.1.0

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.10    digest_0.6.11   rprojroot_1.2   R6_2.2.0        jsonlite_1.4    backports_1.0.5 magrittr_1.5   
 [8] evaluate_0.10   stringi_1.1.2   rmarkdown_1.3   tools_3.3.2     stringr_1.1.0   hms_0.3         yaml_2.1.14    
[15] base64enc_0.1-3 htmltools_0.3.5 knitr_1.15.1    tibble_1.3.0   

The ETL Script

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source("states_ETLscript.R")
Parsed with column specification:
cols(
  .default = col_integer(),
  State = col_character(),
  `MLS Librarians` = col_double(),
  Librarians = col_double(),
  Employees = col_double(),
  `Total Staff` = col_double(),
  `Downloadable Audio` = col_double(),
  `Downloadable Video` = col_double(),
  `Start Date` = col_character(),
  `End Date` = col_character()
)
See spec(...) for full column specifications.
Classes ‘tbl_df’, ‘tbl’ and 'data.frame':   51 obs. of  62 variables:
 $ Submission Year                      : int  2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 ...
 $ State                                : chr  "AK" "AL" "AR" "AZ" ...
 $ State Code                           : int  2 1 5 4 6 8 9 11 10 12 ...
 $ Region Code                          : int  8 5 5 6 8 7 1 2 2 5 ...
 $ Service Population                   : int  652274 4822023 2833849 10501253 38322887 5238320 4374214 658893 925244 19813366 ...
 $ Service Population Without Duplicates: int  652274 4822023 2643928 6667241 38322887 5177510 3596080 658893 925244 19464451 ...
 $ State Population                     : int  735601 4822023 2915918 6667241 38340074 5264890 3596080 658893 925244 19839251 ...
 $ Central Libraries                    : int  85 221 54 85 167 97 192 1 19 63 ...
 $ Branch Libraries                     : int  16 76 179 135 950 162 47 25 13 468 ...
 $ Bookmobiles                          : int  1 14 2 11 53 13 4 0 2 24 ...
 $ MLS Librarians                       : num  58.8 329.6 142 461.3 2976.5 ...
 $ Librarians                           : num  113 736 286 546 3210 ...
 $ Employees                            : num  191 1081 767 1485 8388 ...
 $ Total Staff                          : num  303 1817 1053 2032 11598 ...
 $ Local Government Operating Revenue   : int  32474960 88056291 64665467 157746903 1265099905 265575219 168823962 53095222 19805621 461436699 ...
 $ State Government Operating Revenue   : int  1176158 4736727 5495428 1611605 13614724 1233937 1618933 0 3997939 22913457 ...
 $ Federal Government Operating Revenue : int  1166883 1081174 0 2029032 4633053 772338 330504 912671 2053 1181115 ...
 $ Other Operating Revenue              : int  3122020 9247116 4633340 7024609 71630786 16374433 24624113 180898 1861803 20302059 ...
 $ Total Operating Revenue              : int  37940021 103121308 74794235 168412149 1354978468 283955927 195397512 54188791 25667416 505833330 ...
 $ Salaries                             : int  13969263 54292921 33653433 77164201 565090291 129272590 114615887 31828080 12628074 225861289 ...
 $ Benefits                             : int  9212580 14390910 10389231 28609129 281367947 36756147 33333225 6851322 4724159 81550783 ...
 $ Total Staff Expenditures             : int  23181843 68683831 44042664 105773330 846458238 166028737 147949112 38679402 17352233 307412072 ...
 $ Print Collection Expenditures        : int  2276916 6505277 5533401 14556902 68898041 16445553 12363802 2000732 1797136 33012867 ...
 $ Digital Collection Expenditures      : int  488715 1413812 2023580 6231405 24944727 9371697 3577446 1340000 158409 16421139 ...
 $ Other Collection Expenditures        : int  569660 2701279 1895616 5788517 18886309 9594308 3217904 495000 635597 10771442 ...
 $ Total Collection Expenditures        : int  3335291 10620368 9452597 26576824 112729077 35411558 19159152 3835732 2591142 60205448 ...
 $ Other Operating Expenditures         : int  9991895 20658148 18375101 44262826 326843919 61043834 36150456 11798205 5049298 143395285 ...
 $ Total Operating Expenditures         : int  36509029 99962347 71870362 176612980 1286031234 262484129 203258720 54313339 24992673 511012805 ...
 $ Local Government Capital Revenue     : int  4206200 1835628 6288532 7588520 50568512 10236392 9834713 12950000 148240 23899274 ...
 $ State Government Capital Revenue     : int  20786393 0 289274 30000 203848 42120 3037860 0 3142715 558107 ...
 $ Federal Government Capital Revenue   : int  500000 191962 0 55484 74604 0 216618 0 0 0 ...
 $ Other Capital Revenue                : int  1289455 1435752 611755 83500 11337389 3663220 9350986 0 1723942 378930 ...
 $ Total Capital Revenue                : int  26782048 3463342 7189561 7757504 62184353 13941732 22440177 12950000 5014897 24836311 ...
 $ Total Capital Expenditures           : int  18337915 4777481 8489855 3436844 82960891 45987892 26583582 10353699 10029794 27841697 ...
 $ Print Collection                     : int  2434236 9442086 6304377 8229850 65409430 10316703 14577630 1815540 1642715 31602986 ...
 $ Digital Collection                   : int  351606 2714815 532433 1367378 2978360 1390637 1312468 177086 415170 1797802 ...
 $ Audio Collection                     : int  116847 450144 230003 689616 3530931 922877 826586 86416 114600 1947487 ...
 $ Downloadable Audio                   : num  373121 646206 185583 694223 564568 ...
 $ Physical Video                       : int  277268 620827 401308 1116663 5139201 1344808 1122198 140667 175643 3520618 ...
 $ Downloadable Video                   : num  1181 27411 10028 6281 135125 ...
 $ Local Cooperative Agreements         : int  695 974 563 969 3947 2160 1687 74 54 1844 ...
 $ State Licensed Databases             : int  4116 12737 3016 2430 116 0 7606 0 651 4838 ...
 $ Total Licensed Databases             : int  4811 13711 3579 3399 4063 2160 9293 74 705 6682 ...
 $ Print Subscriptions                  : int  5600 8932 10137 14239 92902 25553 21268 2071 4354 43118 ...
 $ Hours Open                           : int  153410 626821 445052 482261 2267921 608043 551274 65208 85420 1244917 ...
 $ Library Visits                       : int  3491307 17217402 10973629 27609711 164300175 32981666 21972583 4230790 3834672 75553933 ...
 $ Reference Transactions               : int  392428 4417062 2282111 5754966 23208453 4208956 3494403 921814 405585 23686241 ...
 $ Registered Users                     : int  358089 2663716 1615238 3118825 21723648 3588616 1647190 359371 379791 10615421 ...
 $ Circulation Transactions             : int  4792662 20526321 14390348 43672067 222788583 64683932 31081616 3938767 6180769 116693486 ...
 $ Interlibrary Loans Provided          : int  27745 427590 28247 324668 3567561 786027 934646 0 842407 98964 ...
 $ Interlibrary Loans Received          : int  28177 412054 26991 367263 3512390 879725 918765 180 816950 125338 ...
 $ Library Programs                     : int  12803 42145 34227 73875 342664 106717 95517 14357 13056 203578 ...
 $ Childrens Programs                   : int  8802 21685 21081 37852 206627 67253 54737 8514 5408 96748 ...
 $ Young Adult Programs                 : int  1528 4844 4620 6702 33645 9064 7381 1566 1197 17006 ...
 $ Library Program Audience             : int  279080 1053347 997901 1472963 9491467 2647097 2003864 284969 256274 4611959 ...
 $ Childrens Program Audience           : int  202322 696970 712783 1034731 6909344 1799469 1226174 225815 175335 2928059 ...
 $ Young Adult Program Audience         : int  25902 77371 88721 109545 531379 151930 112501 15624 17349 314348 ...
 $ Public Internet Computers            : int  998 5302 2596 5593 21735 6407 4355 1000 772 16781 ...
 $ Internet Computer Use                : int  772129 4359414 1970448 8255038 35000501 7395748 4465464 1050623 622515 19076151 ...
 $ Wireless Internet Sessions           : int  479245 15224387 160450 5880952 14252610 6234884 524318 -1 139907 3276803 ...
 $ Start Date                           : chr  "Jan-13" "Oct-13" "Jan-14" "Jul-13" ...
 $ End Date                             : chr  "Jun-14" "Sep-14" "Dec-14" "Jun-14" ...
 - attr(*, "spec")=List of 2
  ..$ cols   :List of 62
  .. ..$ Submission Year                      : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ State                                : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ State Code                           : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Region Code                          : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Service Population                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Service Population Without Duplicates: list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ State Population                     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Central Libraries                    : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Branch Libraries                     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Bookmobiles                          : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ MLS Librarians                       : list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  .. ..$ Librarians                           : list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  .. ..$ Employees                            : list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  .. ..$ Total Staff                          : list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  .. ..$ Local Government Operating Revenue   : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ State Government Operating Revenue   : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Federal Government Operating Revenue : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Other Operating Revenue              : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Total Operating Revenue              : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Salaries                             : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Benefits                             : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Total Staff Expenditures             : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Print Collection Expenditures        : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Digital Collection Expenditures      : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Other Collection Expenditures        : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Total Collection Expenditures        : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Other Operating Expenditures         : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Total Operating Expenditures         : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Local Government Capital Revenue     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ State Government Capital Revenue     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Federal Government Capital Revenue   : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Other Capital Revenue                : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Total Capital Revenue                : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Total Capital Expenditures           : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Print Collection                     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Digital Collection                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Audio Collection                     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Downloadable Audio                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  .. ..$ Physical Video                       : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Downloadable Video                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  .. ..$ Local Cooperative Agreements         : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ State Licensed Databases             : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Total Licensed Databases             : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Print Subscriptions                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Hours Open                           : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Library Visits                       : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Reference Transactions               : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Registered Users                     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Circulation Transactions             : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Interlibrary Loans Provided          : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Interlibrary Loans Received          : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Library Programs                     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Childrens Programs                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Young Adult Programs                 : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Library Program Audience             : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Childrens Program Audience           : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Young Adult Program Audience         : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Public Internet Computers            : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Internet Computer Use                : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Wireless Internet Sessions           : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Start Date                           : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ End Date                             : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  ..$ default: list()
  .. ..- attr(*, "class")= chr  "collector_guess" "collector"
  ..- attr(*, "class")= chr "col_spec"
CREATE TABLE 00_Docstates State varchar2(4000),
 Service Population Without Duplicates varchar2(4000),
 MLS Librarians varchar2(4000),
 Childrens Programs varchar2(4000),
 Childrens Program Audience varchar2(4000),
 Start Date varchar2(4000),
 End Date varchar2(4000),
 Submission Year number(38,4),
 State Code number(38,4),
 Region Code number(38,4),
 Service Population number(38,4),
 Service Population without Duplicates number(38,4),
 State Population number(38,4),
 Central Libraries number(38,4),
 Branch Libraries number(38,4),
 Bookmobiles number(38,4),
 MLS Libraries number(38,4),
 Librarians number(38,4),
 Employees number(38,4),
 Total Staff number(38,4),
 Local Government Operating Revenue number(38,4),
 State Government Operating Revenue number(38,4),
 Federal Government Operating Revenue number(38,4),
 Other Operating Revenue number(38,4),
 Total Operating Revenue number(38,4),
 Salaries number(38,4),
 Benefits number(38,4),
 Benefits number(38,4),
 Total Staff Expenditures number(38,4),
 Print Collection Expenditures number(38,4),
 Digital Collection Expenditures number(38,4),
 Other Collection Expenditures number(38,4),
 Total Collection Expenditures number(38,4),
 Other Operating Expenditures number(38,4),
 Total Operating Expenditures number(38,4),
 Local Government Capital Revenue number(38,4),
 State Government Capital Revenue number(38,4),
 Federal Government Capital Revenue number(38,4),
 Other Capital Revenue number(38,4),
 Total Capital Revenue number(38,4),
 Total Capital Expenditures number(38,4),
 Print Collection number(38,4),
 Digital Collection number(38,4),
 Audio Collection number(38,4),
 Downloadable Audio number(38,4),
 Physical Video number(38,4),
 Downloadable Video number(38,4),
 Local Cooperative Agreements number(38,4),
 State Licensed Databases number(38,4),
 Total Licensed Databases number(38,4),
 Print Subscriptions number(38,4),
 Hours Open number(38,4),
 Library Visits number(38,4),
 Reference Transactions number(38,4),
 Registered Users number(38,4),
 Circulation Transactions number(38,4),
 Interlibrary Loans Provided number(38,4),
 Interlibrary Loans Received number(38,4),
 Library Programs number(38,4),
 Children's Programs number(38,4),
 Young Adult Programs number(38,4),
 Library Program Audience number(38,4),
 Children's Program Audience number(38,4),
 Young Adult Program Audience number(38,4),
 Public Internet Computers number(38,4),
 Internet Computer Use number(38,4),
 Wireless Internet Sessions number(38,4)
 );

Summary of Library Data

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This data set is from kaggle. You can find this data here. It provides detailed information about libraries in each state in the United States.

summary(states)
 Submission_Year    State             State_Code     Region_Code    Service_Population Service_Population_Without_Duplicates
 Min.   :2015    Length:51          Min.   : 1.00   Min.   :1.000   Min.   :  582658   Min.   :  582658                     
 1st Qu.:2015    Class :character   1st Qu.:16.50   1st Qu.:3.000   1st Qu.: 1493456   1st Qu.: 1472869                     
 Median :2015    Mode  :character   Median :29.00   Median :5.000   Median : 4395295   Median : 4395295                     
 Mean   :2015                       Mean   :28.96   Mean   :4.471   Mean   : 6181043   Mean   : 6021934                     
 3rd Qu.:2015                       3rd Qu.:41.50   3rd Qu.:6.000   3rd Qu.: 7475148   3rd Qu.: 6764752                     
 Max.   :2015                       Max.   :56.00   Max.   :8.000   Max.   :38322887   Max.   :38322887                     
 State_Population   Central_Libraries Branch_Libraries  Bookmobiles    MLS_Librarians      Librarians       Employees     
 Min.   :  582658   Min.   :  1.0     Min.   :  3.0    Min.   : 0.00   Min.   :  39.88   Min.   : 112.5   Min.   : 111.0  
 1st Qu.: 1743730   1st Qu.: 63.0     1st Qu.: 38.5    1st Qu.: 3.00   1st Qu.: 144.50   1st Qu.: 284.2   1st Qu.: 376.4  
 Median : 4395295   Median :112.0     Median : 95.0    Median : 7.00   Median : 329.58   Median : 679.9   Median :1210.1  
 Mean   : 6195242   Mean   :177.5     Mean   :150.4    Mean   :12.92   Mean   : 629.70   Mean   : 927.1   Mean   :1788.9  
 3rd Qu.: 6817706   3rd Qu.:237.5     3rd Qu.:207.0    3rd Qu.:17.50   3rd Qu.: 767.76   3rd Qu.:1171.0   3rd Qu.:2340.9  
 Max.   :38340074   Max.   :755.0     Max.   :950.0    Max.   :75.00   Max.   :3437.24   Max.   :4073.9   Max.   :8391.0  
  Total_Staff      Local_Government_Operating_Revenue State_Government_Operating_Revenue Federal_Government_Operating_Revenue
 Min.   :  245.3   Min.   :0.000e+00                  Min.   :        0                  Min.   :      0                     
 1st Qu.:  723.2   1st Qu.:4.424e+07                  1st Qu.:  1205048                  1st Qu.: 247294                     
 Median : 1817.3   Median :1.185e+08                  Median :  4033130                  Median : 497265                     
 Mean   : 2716.0   Mean   :2.016e+08                  Mean   : 16668047                  Mean   : 895589                     
 3rd Qu.: 3519.8   3rd Qu.:2.374e+08                  3rd Qu.: 12342780                  3rd Qu.:1070844                     
 Max.   :12464.9   Max.   :1.265e+09                  Max.   :345037953                  Max.   :5792339                     
 Other_Operating_Revenue Total_Operating_Revenue    Salaries            Benefits         Total_Staff_Expenditures
 Min.   :   180898       Min.   :1.830e+07       Min.   :  8517104   Min.   :   229606   Min.   : 10890655       
 1st Qu.:  4018902       1st Qu.:5.172e+07       1st Qu.: 24806427   1st Qu.:  8439042   1st Qu.: 33433702       
 Median :  9247116       Median :1.306e+08       Median : 62750473   Median : 22988790   Median : 85739263       
 Mean   : 17522202       Mean   :2.367e+08       Mean   :109245728   Mean   : 39733389   Mean   :148979117       
 3rd Qu.: 17584116       3rd Qu.:2.848e+08       3rd Qu.:139643819   3rd Qu.: 45490279   3rd Qu.:190242298       
 Max.   :191656418       Max.   :1.355e+09       Max.   :605134988   Max.   :281367947   Max.   :876111285       
 Print_Collection_Expenditures Digital_Collection_Expenditures Other_Collection_Expenditures Total_Collection_Expenditures
 Min.   : 1732866              Min.   :  158409                Min.   :   76731              Min.   :  2432733            
 1st Qu.: 3703121              1st Qu.: 1161444                1st Qu.:  756074              1st Qu.:  5457850            
 Median :10136582              Median : 2887735                Median : 3217904              Median : 15558992            
 Mean   :14738013              Mean   : 5356909                Mean   : 4911608              Mean   : 25006531            
 3rd Qu.:18743538              3rd Qu.: 6431658                3rd Qu.: 6629340              3rd Qu.: 34862064            
 Max.   :68898041              Max.   :24944727                Max.   :32163245              Max.   :112729077            
 Other_Operating_Expenditures Total_Operating_Expenditures Local_Government_Capital_Revenue State_Government_Capital_Revenue
 Min.   :  3944576            Min.   :1.731e+07            Min.   :       0                 Min.   :       0                
 1st Qu.:  9923100            1st Qu.:4.882e+07            1st Qu.: 1998838                 1st Qu.:       0                
 Median : 26913847            Median :1.260e+08            Median : 7588520                 Median :   49290                
 Mean   : 48396075            Mean   :2.224e+08            Mean   :10798721                 Mean   : 2419471                
 3rd Qu.: 56365576            3rd Qu.:2.680e+08            3rd Qu.:16868779                 3rd Qu.: 1125000                
 Max.   :326843919            Max.   :1.286e+09            Max.   :50568512                 Max.   :25243857                
 Federal_Government_Capital_Revenue Other_Capital_Revenue Total_Capital_Revenue Total_Capital_Expenditures Print_Collection  
 Min.   :       0                   Min.   :       0      Min.   :   190956     Min.   :   347748          Min.   : 1642715  
 1st Qu.:       0                   1st Qu.:  310920      1st Qu.:  4831600     1st Qu.:  5074609          1st Qu.: 4679018  
 Median :   31980                   Median : 1289455      Median :  9698454     Median : 10372327          Median : 9442086  
 Mean   :  495817                   Mean   : 4071006      Mean   : 17785016     Mean   : 22637427          Mean   :15056932  
 3rd Qu.:  211338                   3rd Qu.: 3236141      3rd Qu.: 23468550     3rd Qu.: 28077506          3rd Qu.:17167508  
 Max.   :18521642                   Max.   :87067000      Max.   :116604806     Max.   :126989107          Max.   :70815265  
 Digital_Collection Audio_Collection  Downloadable_Audio Physical_Video    Downloadable_Video Local_Cooperative_Agreements
 Min.   :   22966   Min.   :  86416   Min.   :    9338   Min.   : 119605   Min.   :     0     Min.   :    0               
 1st Qu.:  399830   1st Qu.: 230386   1st Qu.:  222568   1st Qu.: 324603   1st Qu.:  5026     1st Qu.:  395               
 Median : 1647955   Median : 593488   Median :  564568   Median : 814043   Median : 21580     Median :  888               
 Mean   : 4194353   Mean   : 893410   Mean   : 1300921   Mean   :1209907   Mean   :105070     Mean   : 1909               
 3rd Qu.: 3683356   3rd Qu.:1130140   3rd Qu.: 1358018   3rd Qu.:1437894   3rd Qu.: 71680     3rd Qu.: 1865               
 Max.   :47106859   Max.   :3530931   Max.   :11064932   Max.   :5154677   Max.   :922536     Max.   :17442               
 State_Licensed_Databases Total_Licensed_Databases Print_Subscriptions   Hours_Open      Library_Visits     
 Min.   :    0            Min.   :   74            Min.   :  2071      Min.   :  65208   Min.   :  2186038  
 1st Qu.: 1785            1st Qu.: 2810            1st Qu.:  6368      1st Qu.: 293115   1st Qu.:  7430782  
 Median : 4275            Median : 5003            Median : 14972      Median : 551274   Median : 18178677  
 Mean   : 6252            Mean   : 8161            Mean   : 26915      Mean   : 721113   Mean   : 27947560  
 3rd Qu.: 8093            3rd Qu.:11726            3rd Qu.: 36913      3rd Qu.: 922803   3rd Qu.: 35273654  
 Max.   :26371            Max.   :28951            Max.   :166683      Max.   :2392554   Max.   :164300175  
 Reference_Transactions Registered_Users   Circulation_Transactions Interlibrary_Loans_Provided Interlibrary_Loans_Received
 Min.   :  373837       Min.   :  281392   Min.   :  3938767        Min.   :       0            Min.   :      57           
 1st Qu.:  911614       1st Qu.:  924534   1st Qu.:  9299584        1st Qu.:   57346            1st Qu.:   62142           
 Median : 3483395       Median : 2476596   Median : 27866711        Median :  266163            Median :  302038           
 Mean   : 5157088       Mean   : 3372037   Mean   : 45376494        Mean   : 1385314            Mean   : 1382256           
 3rd Qu.: 6240569       3rd Qu.: 4122706   3rd Qu.: 61758828        3rd Qu.:  906895            3rd Qu.:  901136           
 Max.   :28105028       Max.   :21723648   Max.   :222788583        Max.   :11912575            Max.   :11469527           
 Library_Programs Childrens_Programs Young_Adult_Programs Library_Program_Audience Childrens_Program_Audience
 Min.   :  7940   Min.   :  5265     Min.   : 1172        Min.   : 183507          Min.   : 145049           
 1st Qu.: 25835   1st Qu.: 15432     1st Qu.: 2356        1st Qu.: 609558          1st Qu.: 388609           
 Median : 62120   Median : 37852     Median : 6168        Median :1396310          Median :1032396           
 Mean   : 87964   Mean   : 50464     Mean   : 8322        Mean   :2000421          Mean   :1376584           
 3rd Qu.:101758   3rd Qu.: 64567     3rd Qu.: 9664        3rd Qu.:2450672          3rd Qu.:1725636           
 Max.   :500005   Max.   :213468     Max.   :55526        Max.   :9491467          Max.   :6909344           
 Young_Adult_Program_Audience Public_Internet_Computers Internet_Computer_Use Wireless_Internet_Sessions  Start_Date       
 Min.   : 12589               Min.   :  524             Min.   :  577405      Min.   :      -1           Length:51         
 1st Qu.: 33708               1st Qu.: 1556             1st Qu.: 1895499      1st Qu.:  198808           Class :character  
 Median : 94146               Median : 4726             Median : 4465464      Median : 1266660           Mode  :character  
 Mean   :131304               Mean   : 5610             Mean   : 6320727      Mean   : 2926421                             
 3rd Qu.:160931               3rd Qu.: 6724             3rd Qu.: 7600968      3rd Qu.: 4223684                             
 Max.   :725295               Max.   :21735             Max.   :35000501      Max.   :15224387                             
   End_Date        
 Length:51         
 Class :character  
 Mode  :character  
                   
                   
                   

Summary of Subsets of Library Data

Back To Top

This data is a subset of the library data that was re-configured to make Digital Cost, Other Cost, Print Cost, and Total Cost to be a subset of a larger category – Collection Cost Type. This way, the data could be easily grouped on the same visualization.

summary(states_boxplot)
    State             Category              Cost          
 Length:204         Length:204         Min.   :    76731  
 Class :character   Class :character   1st Qu.:  2429076  
 Mode  :character   Mode  :character   Median :  5843598  
                                       Mean   : 12503265  
                                       3rd Qu.: 15685597  
                                       Max.   :112729077  

This data is a subset of the library data that was re-configured to make Children’s Programs, Young Adult Programs, and Adult Programs to be a subset of a larger category – Program Type. This way, the data could be easily grouped on the same visualization.

summary(Program_Category)
    State           Program_Category    Num_Programs   
 Length:153         Length:153         Min.   :  1172  
 Class :character   Class :character   1st Qu.:  7381  
 Mode  :character   Mode  :character   Median : 22070  
                                       Mean   : 48917  
                                       3rd Qu.: 62120  
                                       Max.   :500005  

Summary of Census Data

Back To Top

This data set is from the census data on data.world. You can find this data here. It provides the number of employed persons in each state.

summary(census_employment)
    State              Employed       
 Length:52          Min.   :  456640  
 Class :character   1st Qu.: 1398759  
 Mode  :character   Median : 3335384  
                    Mean   : 4886644  
                    3rd Qu.: 5501786  
                    Max.   :30312429  

This data set is from the census data on data.world. You can find this data here. It provides the number of people enrolled in high school in each state.

summary(census_enrollment)
    State           Enrollment_9to12 
 Length:52          Min.   :  24198  
 Class :character   1st Qu.:  91860  
 Mode  :character   Median : 215712  
                    Mean   : 331031  
                    3rd Qu.: 362992  
                    Max.   :2216175  

This data set is from the census data on data.world. You can find this data here. It provides the median family income in each state.

summary(Median_Family_Income)
    State             B19119_001   
 Length:52          Min.   :22976  
 Class :character   1st Qu.:57986  
 Mode  :character   Median :65813  
                    Mean   :66551  
                    3rd Qu.:74030  
                    Max.   :90089  

This data set is from Current Results. You can find this data here. It provides the average temperature in each state.

summary(State_Temp_and_Rain)
    State           Average Temperature Total Hours of Sunlight   Clear Days    
 Length:50          Min.   :26.60       Min.   :2061            Min.   : 58.00  
 Class :character   1st Qu.:45.25       1st Qu.:2514            1st Qu.: 89.25  
 Mode  :character   Median :51.20       Median :2690            Median :100.50  
                    Mean   :51.94       Mean   :2721            Mean   :103.26  
                    3rd Qu.:58.65       3rd Qu.:2924            3rd Qu.:115.00  
                    Max.   :70.70       Max.   :3806            Max.   :193.00  
                                        NA's   :3                               

This data set is from Researcher Tools. You can find this data here. It provides useful connections between state names, state codes, and regions.

summary(states_with_regions)
    State            State Code           Region           Sub-Region       
 Length:50          Length:50          Length:50          Length:50         
 Class :character   Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character   Mode  :character  

The Tableau Visualizations

Back To Top

Map of the United States color-coded by region. This is an interactive map that allows you to filter what is shown on sheet Library Programs vs. Visits and Program Breakdown by Type.

Dual combination showing the number of library programs per 10,000 people and the annual visits per capita for each state. Two calculated measured were created for this visualization.

  1. Library_programs_per_10K = [Library_Programs] *10000 / [State_Population]
  2. Library_visits_per_capita = [Library_Visits] / [State_Population]

Additionally, a set was created to show High Visit States which is a grouping of states who average more than 5.5 visits per person per year.

The South region has zero states in the High Visit States set. The other three regions have either 4 or 5 states each. This implies that libraries in the south could benefit from talking to the other regions about the kinds of programs they are implementing to get people to go to the library. Additionally, the states in the southern region have noticeably fewer library programs per 10,000 residents. Looking at all of the regions, there is a general positive correlation between the number of programs per 10,000 people and the average number of visits per person. Therefore, if a state wanted to increase the number of visits to public libraries a larger budget could be allocated for library programs.

A stacked bar graph showing the percentage breakdown of total library programs into those for children, adolescents, and those for adults. To determine this, three measure calculations were used, however, these were not stored as new measures. These calculations changed the data from number of programs to a percentage of total programs for each of the three program categories.

  1. Calculation for percent children programs: [Childrens_programs] / [Library_programs]
  2. Calculation for percent adolescent programs: [Young_adult_programs] / [Library_programs]
  3. Calculation for percent adult programs: [Adult_programs] / [Library_programs]

In general, if less than 58% of states library programs are aimed at children then the annual number of visits per capita is lower. Additionally, southern states (on average) offer a lower percentage of children programs than the other three regions. This could be a contributing factor to the lower number of visits to libraries in the south.

This is a dashboard for the previous three visualizations.

Box and whisker plot showing the total digital collection cost, print collection cost, other collection cost, and total collection cost for each state. The visualization has four pages, one for each region.

All four regions spend the most on print collections with digital and other (such as audio) collection costs being roughly similar. Heavily populated states (Texas, California, New York, Ohio) fall outside the interquartile range for collection costs due to the significantly increased volume of collection material required in these larger states.

Scatterplot showing the relationship between the total collection cost and size for each state color-coded by region with a trendline for each region.

From the regional trend lines on this visualization, it can be seen that Midwest and Northeast spend less per collection item than South and West regions. The South and West regions should consult with the material procurement teams in the Midwest and Northeast regions to determine how to reduce collection costs.

This is a dashboard for the previous two visualizations.

A scatter plot showing how the average annual temperature in a state is related to the average annual visits per capita. The average annual visits per capita was found using the following formula: [Library_Visits]/[State_Population]. The points are color-coded by region and have a trend line with a 95% confidence bands.

There is a general trend that the higher the average temperature in a state the fewer number of visits per capita to the libraries. This is a logical, yet interesting result, as warmer temperatures lend themselves more towards being active and outdoors than attending the library.

A crosstab of operational revenue to cost ratio. A red-green scale was used to color the average ratio value of Profit to Expense Ratio with a ratio of 1.0 selected as the transition point between the colors. The crosstab is created with values given by state and separated by sub-region.

Profit to Expense Ratio = [Total_Operating_Revenue]/[Total_Operating_Expenditures]

New England has the lowest revenue to cost ratio. Most of the region’s libraries are profiting but no library is particularly profitable.

A filled map of the United States showing the average number of computers per library for each state. A KPI was created for this statistic and the filled color of each individual state is coordinated to whether or not the KPI is low, medium, or high and the range for each category of the KPI can be adjusted by the user. KPI Low was set to 12 and KPI Medium is set to 19.

KPI Computers per Library =

IF AVG([Public_Internet_Computers] / ([Central_Libraries] + [Branch_Libraries])) <= [KPI Low] THEN “Low” ELSEIF AVG([Public_Internet_Computers] / ([Central_Libraries] + [Branch_Libraries])) <= [KPI Medium] THEN “Medium” ELSE “High” END

KPI Low: ranges from 1 to 12 KPI Medium: ranges from 13 to 20

The midwest has the least computers per library compared to other regions. The South has the most computers per library.

A histogram of showing the annual computer usage and the states that fall into each bin with the bin size being 2.5 million. The columns are labelled with each state fall into the bin. Annual computer usage is measured in number of sessions logged.The KPI Computers per Library was used again in this case. KPI Low was set to 12 and KPI Medium is set to 19.

States that have medium to high amounts of amounts of computers per libraries (blue and red blocks) also tend to have higher amounts of computer usage. This could indicate that the extra computers available to the public allow for more computer usage.

This is a dashboard for the previous two visualizations.

The Shiny Visualizations

Back To Top

This boxplot shows the minimum, maximum, first quartile, third quartile, and median of the “Cost” values for each expenditure, including Digital Collection Expenditures, Print Collection Expenditures, Other Expenditures, and Total Expenditures. The user may select the “Cost Range” that they would like to see.

This is interesting because you can see how many states are outliers in spending on Digital and Print Expenditures.

This histogram shows the number of Librarians in each state.

This is interesting because you can see the overall trend of lot of states having relatively little Librarians (>300), while one state, New York, has almost a thousand more librarians than the second highest state, CA, created a gap in the histogram.

This graph shows how different states compare in terms of Library Visits per Median Family Income. This uses a join with the 2015 Census data.

This is interesting because it shows a trend that richer states have more library visits. We were surprised by this because libraries provide many services for free that would benefit low income families.

This graph shows the Cost per Category per State. The graph is the colored according to the table calculation: sum(Library_Visits) /sum(Service_Population_Without_Duplicates. The limits for the KPI can be selected by the user.

This is interesting because you can see that Texas has some of the highest library costs in the country, but still has a relatively low number of visitors per service population.

This graph shows the number of Librarians per State, and the fill of the graph is colored according to the table calculation of the number of citizens per Librarian.

This is interesting because you can see that GA has a relatively low number of overall librarians, but has by far the highest ratio of librarians per citizen.

This graph shows compares the total open library hours and the high school enrollment in each state.

This is interesting because, generally speaking, the states with the highest hours open have the highest high school enrollment.

---
title: "The Library System of the United States"
subtitle: "Data Visualization -- Final Project"
author: "Hannah Brinsko, Haley Folkes, Sarah Moor, and Kevin Pappas"
date: "Wednesday, May 3, 2017"
output:
  html_document:
    toc: yes
  html_notebook:
    toc: yes
---

![\n](books_image.png)

## Important Resources and Links
<a href="#top">Back To Top</a>

To see our GitHub repository, click [here](https://github.com/CannataUTDV/s17dvfinalproject-folkes-moor-brinsko-pappas).

To see our Shiny application, click [here](https://hbrinsko.shinyapps.io/finalproject).

## Session Information
<a href="#top">Back To Top</a>

```{r sessionInfo}
sessionInfo(package=NULL)
```

## The ETL Script
<a href="#top">Back To Top</a>

```{r etl}
source("states_ETLscript.R")
```

## Summary of Library Data
<a href="#top">Back To Top</a>

This data set is from kaggle. You can find this data [here](https://www.kaggle.com/imls/public-libraries). It provides detailed information about libraries in each state in the United States.

```{r states}
summary(states)
```

## Summary of Subsets of Library Data
<a href="#top">Back To Top</a>

This data is a subset of the library data that was re-configured to make Digital Cost, Other Cost, Print Cost, and Total Cost to be a subset of a larger category -- Collection Cost Type. This way, the data could be easily grouped on the same visualization.

```{r states_boxplot}
summary(states_boxplot)
```

This data is a subset of the library data that was re-configured to make Children's Programs, Young Adult Programs, and Adult Programs to be a subset of a larger category -- Program Type. This way, the data could be easily grouped on the same visualization.

```{r Program_Category}
summary(Program_Category)
```

## Summary of Census Data
<a href="#top">Back To Top</a>

This data set is from the census data on data.world. You can find this data [here](https://data.world/uscensusbureau/acs-2015-5-e-employmentstatus/file/USA_All_States.csv). It provides the number of employed persons in each state.

```{r census_employment}
summary(census_employment)
```

This data set is from the census data on data.world. You can find this data [here](https://data.world/uscensusbureau/acs-2015-5-e-schoolenrollment/file/USA_All_States.csv). It provides the number of people enrolled in high school in each state.

```{r census_enrollment}
summary(census_enrollment)
```

This data set is from the census data on data.world. You can find this data [here](https://data.world/uscensusbureau/acs-2015-5-e-income/USA_All_States.csv). It provides the median family income in each state.

```{r Median_Family_Income}
summary(Median_Family_Income)
```

This data set is from Current Results. You can find this data [here](https://www.currentresults.com/Weather/US/average-annual-state-temperatures.php). It provides the average temperature in each state.

```{r State_Temp_and_Rain}
summary(State_Temp_and_Rain)
```

This data set is from Researcher Tools. You can find this data [here](http://researchertools.blogspot.com/2012/09/excel-file-with-us-states-abbreviations.html). It provides useful connections between state names, state codes, and regions. 

```{r states_with_regions}
summary(states_with_regions)
```

## The Tableau Visualizations
<a href="#top">Back To Top</a>

Map of the United States color-coded by region. This is an interactive map that allows you to filter what is shown on sheet Library Programs vs. Visits and Program Breakdown by Type.   
![\n](Filled_US_State_Map.png)

Dual combination showing the number of library programs per 10,000 people and the annual visits per capita for each state. Two calculated measured were created for this visualization. 

1) Library_programs_per_10K = [Library_Programs] *10000 / [State_Population]
2) Library_visits_per_capita = [Library_Visits] / [State_Population]

Additionally, a set was created to show High Visit States which is a grouping of states who average more than 5.5 visits per person per year.

The South region has zero states in the High Visit States set. The other three regions have either 4 or 5 states each. This implies that libraries in the south could benefit from talking to the other regions about the kinds of programs they are implementing to get people to go to the library. Additionally, the states in the southern region have noticeably fewer library programs per 10,000 residents. Looking at all of the regions, there is a general positive correlation between the number of programs per 10,000 people and the average number of visits per person. Therefore, if a state wanted to increase the number of visits to public libraries a larger budget could be allocated for library programs.
![\n](Dual_Combination_Programs_Visits.png)

A stacked bar graph showing the percentage breakdown of total library programs into those for children, adolescents, and those for adults. To determine this, three measure calculations were used, however, these were not stored as new measures. These calculations changed the data from number of programs to a percentage of total programs for each of the three program categories. 

1) Calculation for percent children programs: [Childrens_programs] / [Library_programs]
2) Calculation for percent adolescent programs: [Young_adult_programs] / [Library_programs]
3) Calculation for percent adult programs: [Adult_programs] / [Library_programs]

In general, if less than 58% of states library programs are aimed at children then the annual number of visits per capita is lower. Additionally, southern states (on average) offer a lower percentage of children programs than the other three regions. This could be a contributing factor to the lower number of visits to libraries in the south. 
![\n](Stacked_bar_program_breakdown.png)

This is a dashboard for the previous three visualizations.
![\n](Dashboard_Library_programs_vs_Visits.png)

Box and whisker plot showing the total digital collection cost, print collection cost, other collection cost, and total collection cost for each state. The visualization has four pages, one for each region.

All four regions spend the most on print collections with digital and other (such as audio) collection costs being roughly similar. Heavily populated states (Texas, California, New York, Ohio) fall outside the interquartile range for collection costs due to the significantly increased volume of collection material required in these larger states.
![\n](box_and_whisker_collection_costs.png)

Scatterplot showing the relationship between the total collection cost and size for each state color-coded by region with a trendline for each region.

From the regional trend lines on this visualization, it can be seen that Midwest and Northeast spend less per collection item than South and West regions. The South and West regions should consult with the material procurement teams in the Midwest and Northeast regions to determine how to reduce collection costs.
![\n](Scatterplot_collection_cost_and_size.png)

This is a dashboard for the previous two visualizations.
![\n](Dashboard_Collection_Cost_vs_Size.png)

A scatter plot showing how the average annual temperature in a state is related to the average annual visits per capita. The average annual visits per capita was found using the following formula: [Library_Visits]/[State_Population]. The points are color-coded by region and have a trend line with a 95% confidence bands.

There is a general trend that the higher the average temperature in a state the fewer number of visits per capita to the libraries. This is a logical, yet interesting result, as warmer temperatures lend themselves more towards being active and outdoors than attending the library. 
![\n](Scatterplot_Annual_Temp_vs_Visits.png)

A crosstab of operational revenue to cost ratio. A red-green scale was used to color the average ratio value of Profit to Expense Ratio with a ratio of 1.0 selected as the transition point between the colors. The crosstab is created with values given by state and separated by sub-region.

Profit to Expense Ratio = [Total_Operating_Revenue]/[Total_Operating_Expenditures]
	
New England has the lowest revenue to cost ratio. Most of the region's libraries are profiting but no library is particularly profitable.
![\n](Crosstab_revenue_cost_ratio.png)

A filled map of the United States showing the average number of computers per library for each state. A KPI was created for this statistic and the filled color of each individual state is coordinated to whether or not the KPI is low, medium, or high and the range for each category of the KPI can be adjusted by the user. KPI Low was set to 12 and KPI Medium is set to 19.

KPI Computers per Library =

IF AVG([Public_Internet_Computers] / ([Central_Libraries] + [Branch_Libraries])) <= [KPI Low] THEN "Low"
ELSEIF AVG([Public_Internet_Computers] / ([Central_Libraries] + [Branch_Libraries])) <= [KPI Medium] THEN "Medium"
ELSE "High"
END

KPI Low: ranges from 1 to 12
KPI Medium: ranges from 13 to 20

The midwest has the least computers per library compared to other regions. The South has the most computers per library. 
![\n](Filled_map_computers_kpi.png)

A histogram of showing the annual computer usage and the states that fall into each bin with the bin size being 2.5 million. The columns are labelled with each state fall into the bin. Annual computer usage is measured in number of sessions logged.The KPI Computers per Library was used again in this case. KPI Low was set to 12 and KPI Medium is set to 19.

States that have medium to high amounts of amounts of computers per libraries (blue and red blocks) also tend to have higher amounts of computer usage. This could indicate that the extra computers available to the public allow for more computer usage.

![\n](Histogram_computer_use.png)

This is a dashboard for the previous two visualizations.
![\n](Dashboard_Computer_Count_and_Usage.png)

## The Shiny Visualizations
<a href="#top">Back To Top</a>

This boxplot shows the minimum, maximum, first quartile, third quartile, and median of the "Cost" values for each expenditure, including Digital Collection Expenditures, Print Collection Expenditures, Other Expenditures, and Total Expenditures. The user may select the "Cost Range" that they would like to see. 

This is interesting because you can see how many states are outliers in spending on Digital and Print Expenditures.

![\n](Boxplot.png)

This histogram shows the number of Librarians in each state.

This is interesting because you can see the overall trend of lot of states having relatively little Librarians (>300), while one state, New York, has almost a thousand more librarians than the second highest state, CA, created a gap in the histogram.

![\n](Histogram.png)

This graph shows how different states compare in terms of Library Visits per Median Family Income. This uses a join with the 2015 Census data. 

This is interesting because it shows a trend that richer states have more library visits. We were surprised by this because libraries provide many services for free that would benefit low income families.

![\n](Scatterplot.png)

This graph shows the Cost per Category per State. The graph is the colored according to the table calculation: sum(Library_Visits) /sum(Service_Population_Without_Duplicates. The limits for the KPI can be selected by the user.

This is interesting because you can see that Texas has some of the highest library costs in the country, but still has a relatively low number of visitors per service population.

![\n](Crosstab.png)

This graph shows the number of Librarians per State, and the fill of the graph is colored according to the table calculation of the number of citizens per Librarian. 


This is interesting because you can see that GA has a relatively low number of overall librarians, but has by far the highest ratio of librarians per citizen. 

![\n](Barchart.png)

This graph shows compares the total open library hours and the high school enrollment in each state.

This is interesting because, generally speaking, the states with the highest hours open have the highest high school enrollment. 

![\n](Barchart2.png)


